The World According to
Wavelets: The Story of a Mathematical Technique in the Making, Barbara
Burke Hubbard. A very accessible book on the history and applications
of wavelets. Not the best book to learn about the details of their
mathematics or algorithms, however.

Numerical Analysis,
2nd edition, David Kincaid and Ward Cheney. One of the best textbooks
on numerical analysis (which is a subtopic of scientific computing, more
focused on error analysis and derivation of algorithms than on their
applications).

Applied Numerical Linear Algebra, James Demmel,
More focused and more current than
Golub's book. Does a nice job of comparing algorithms.

The Geometry Toolbox for Graphics and Modeling,
Gerald Farin and Dianne Hansford, Not really a
scientific computing book. The best presentations I've seen of
geometric explanations and intuition for matrices, eigenvalues,
and other
linear algebra concepts. Aimed at freshman/sophomore undergrad level,
but useful for anyone who uses this stuff.

A Multigrid Tutorial,
2nd edition, William L. Briggs, Van Emden Henson,
Steve F. McCormick. Best book on this particular way of solving
certain PDE & linear systems. Multigrid methods are extremely fast,
when they work, but they're not applicable to all problems.

Ordinary Differential Equations, V. I. Arnold.
Not numerically oriented, but has great
sketches of diff. eq's.

Differential Equations with Applications and Historical Notes,
George F. Simmons.
An excellent textbook, also not numerically oriented.

The survey paper
Mesh Generation,
Marshall Bern and David Eppstein,
Handbook of Computational Geometry, Elsevier, 2000,
is available
at Shewchuck's site
(The copy I distributed in class 12/7,
from Eppstein,
seems to be older.)